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Matematicheskaya Biologiya i Bioinformatika, 2017, Volume 12, Issue 2, Pages 536–545
DOI: https://doi.org/10.17537/2017.12.536
(Mi mbb311)
 

This article is cited in 4 scientific papers (total in 4 papers)

Information and Computing Technologies in Biology and Medicine

Non-invasive arterial pressure estimating with the cardiac monitor CardioQvark

O. V. Senko, V. Ya. Chuchupal, A. A. Dokukin

Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, Moscow, Russia
Full-text PDF (395 kB) Citations (4)
References:
Abstract: The outcome of the research on possibility to non-invasively estimate systolic blood pressure is presented. The estimating was performed by applying machine learning techniques to the data acquired with the cardiac monitor CardioQvark. The developed in Russia cardiac monitor represents a portable device capable of registering synchronous electrocardiogram and photoplethysmogram. The presented results confirm the possibility of constructing algorithms capable of estimating systolic blood pressure of individual patients. Also the possibility to construct general purpose algorithms, i.e. algorithms capable of estimating blood pressure of any patient without additional setup, was confirmed.
Key words: non-invasive estimating, arterial pressure, electrocardiogram, photoplethysmogram, machine learning, cardiac monitor, CardioQvark.
Funding agency Grant number
Russian Foundation for Basic Research 17-07-01362_а
18-01-00557
Received 21.11.2017, Published 15.12.2017
Document Type: Article
UDC: 004.852
Language: Russian
Citation: O. V. Senko, V. Ya. Chuchupal, A. A. Dokukin, “Non-invasive arterial pressure estimating with the cardiac monitor CardioQvark”, Mat. Biolog. Bioinform., 12:2 (2017), 536–545
Citation in format AMSBIB
\Bibitem{SenChuDok17}
\by O.~V.~Senko, V.~Ya.~Chuchupal, A.~A.~Dokukin
\paper Non-invasive arterial pressure estimating with the cardiac monitor CardioQvark
\jour Mat. Biolog. Bioinform.
\yr 2017
\vol 12
\issue 2
\pages 536--545
\mathnet{http://mi.mathnet.ru/mbb311}
\crossref{https://doi.org/10.17537/2017.12.536}
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  • This publication is cited in the following 4 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
     
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